aspects of OOP in Python

Description

Write an Earthquake class that demonstrates the following aspects of OOP in Python:

1. Create a basic class that can hold all relevant earthquake data saved in index.sqlite see below
2. Appropriately create a constructor to set all data values .
3. Create a regular class method that returns all or part of the Earthquake data as a dictionary object.
4. Override the __str__ method to print a reasonable string representation of an Earthquake.
5. Use the @property decorator to make at least one property in your Earthquake class private.
6. Use the @???.setter method to validate the private property in some way (e.g. check if its numeric, change it’s data type, change it’s length…) before setting its value.

Write a second class called Point, Position or Time to store one or more pieces of earthquake data.This class can be included in the Earthquake.py file.

• The class could store latitude & longitude OR latitude and longitude and depth OR timestamp
• You should use this class in the Earthquake class instead of storing the vales as primitive data types
• This class should include an __init__ method and a __str__ method.  If you create class to stor time, the __str__ method should return a formatted string, not a timestamp.

You may use the Author and Article classes presented in lecture as a starting point for these classes.

Earthquake_stats.py

Write an Earthquake_stats class that uses the Earthquake object AND a Pandas dataframe to process earthquake data and display basic statistics.

• You should import the Earthquake module to use in this application.
• You will read Earthquakes from the database, just like in stats.py,  but instead of putting them into individual lists for each type of date, you will create a list of Earthquake objects.
• You will  list of earthquake objects to a Panda’s Dataframe.

o   See https://stackoverflow.com/questions/47623014/converting-a-list-of-objects-to-a-pandas-dataframe (Links to an external site.) for an example of how to use a custom method to turn you object into a dictionary AND use list comprehension to create a list of Earthquake dictionaries to create your DataFrame.

• Display either the first 5 or last 5 earthquakes in the dataframe to the screen.
• Use the dataframe to compute basic statistics for the entire population of earthquakes
• Compute the same basic statistics for earthquakes filtered on Region. Computer a separate set of statistics for two different regions that have at least 200 earthquakes in your sample.
• Compute the same basic statistics for all earthquakes filtered by either felt, tsunami or depth
  e.g felt > 0, tsunami > 0, depth < 50 or depth<100.